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A Blueprint for Modern Floodplain Management: System Requirements and Architecture for AI-Ready Platforms

A Blueprint for Modern Floodplain Management: System Requirements and Architecture for AI-Ready Platforms

This is a Preprint and has not been peer reviewed. This is version 1 of this Preprint.

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Authors

Dilara Kizilkaya, Yusuf Sermet, Ibrahim Demir

Abstract

Floodplain managers play a critical role in mitigating flood risks and ensuring compliance with federal, state, and local regulations. Their daily work often depends on a patchwork of standalone tools, manual processes, and legacy systems that have evolved over time to meet regulatory and community needs. To establish a foundation for next-generation technological solutions, we synthesized insights from a multi-tiered requirements elicitation process involving the analysis of continental U.S. local ordinances, professional consultations, and iterative community validation at targeted domain venues. This domain survey revealed five recurring themes spanning data use, workflow efficiency, communication challenges, regulatory complexity, and openness to technological innovation. The domain input identified a heavy reliance on FEMA maps with limited integration capabilities, widespread manual documentation, and significant barriers to public engagement and cross-jurisdictional tool adoption. It also identified opportunities for improvement, including enhanced GIS overlays, streamlined permit automation, scenario-based modeling, real-time alerts, and elevation verification tools. Drawing on these insights, we propose design principles for intelligent, user-centered platforms that integrate local workflows, regulatory requirements, and citizen engagement. This work establishes a highly practical, forward-thinking blueprint for democratizing AI-ready hydrology tools across resource-constrained local governments.

DOI

https://doi.org/10.31223/X5Q50N

Subjects

Artificial Intelligence and Robotics, Civil and Environmental Engineering, Computer Sciences, Engineering, Hydraulic Engineering, Physical Sciences and Mathematics, Water Resource Management

Keywords

Floodplain Management, Artificial Intelligence, Decision Support Systems, Requirements Engineering, Hydrology, Flood Risk Management, Large Language Models, Geographic Information Systems

Dates

Published: 2026-07-29 10:41

Last Updated: 2026-07-30 05:39

License

CC BY Attribution 4.0 International

Additional Metadata

Conflict of interest statement:
None

Data Availability:
The data supporting the findings of this study consist of publicly available floodplain management regulations, publicly accessible documentation, and synthesized observations from domain engagement. Additional supporting materials are available from the corresponding author upon reasonable request.

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